Diabetology & Metabolic Syndrome (Jun 2019)

Assessment of the relationship between serum uric acid and glucose levels in healthy, prediabetic and diabetic individuals

  • Tangigul Haque,
  • Sadaqur Rahman,
  • Shiful Islam,
  • Noyan Hossain Molla,
  • Nurshad Ali

DOI
https://doi.org/10.1186/s13098-019-0446-6
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 8

Abstract

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Abstract Background In epidemiological studies, serum uric acid (SUA) has been shown to be associated with hypertension and cardiovascular disorders. However, limited studies have evaluated the relationship between SUA and glucose levels in healthy and diabetic individuals and their observed findings are inconsistent. This study aimed to examine the relationship between SUA and fasting blood glucose (FBG) levels among healthy, prediabetic and diabetic individuals in Bangladesh. Methods In total, 310 blood samples were collected from 215 male and 95 female subjects and analyzed for FBG, SUA, and lipid levels. All participants were categorized into four quartiles based on SUA concentrations. Diabetes and prediabetes were defined as FBG level ≥ 126 mg/dL and 100–125 mg/dL, respectively. The association between SUA and diabetes was evaluated by multinomial logistic regression analysis. Results The prediabetic and diabetic individuals had a lower mean level of SUA (338.2 ± 101.6 and 290.9 ± 98.2 µmol/L, respectively) compared to healthy (369.5 ± 110.9 µmol/L) individuals (p < 0.001). SUA was positively associated with BMI, TG and TC but negatively associated with FBG. The prevalence of diabetes was decreased with increasing concentration of SUA across the quartiles. In regression analysis, SUA levels were inversely associated with diabetes mellitus. Conclusions SUA levels were high in healthy individuals but declined in prediabetic and diabetic individuals with increasing FBG concentrations. A significant inverse association was observed between the levels of SUA and diabetes in Bangladeshi adults. Further studies are needed to examine the reliability of using SUA to predict diabetes.

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